refresh_matchesMatch the account's CV against the vacancies added since it last looked, in the background. Idempotent and cheap when nothing is new. force=true runs a full re-match regardless.
| Name | Required | Description | Default |
|---|---|---|---|
| force | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states 'Idempotent and cheap when nothing is new,' but the annotations set idempotentHint to false. This is a direct contradiction between the description and the structured metadata, which undermines reliability and warrants the lowest transparency score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: the main action is in the first sentence, followed by two short sentences that add meaningful behavioral and parameter detail. Every sentence earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter background trigger with no output schema, the description covers the operation, the force flag, and the idempotency/no-op behavior. It does not mention how an agent would discover results or status afterwards, but given the low complexity and sibling tools like get_match_status, this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates for the single parameter by explaining that force=true runs a full re-match regardless. It also clarifies the default incremental behavior through the first sentence, so the agent understands exactly what the parameter does.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: match the account's CV against vacancies added since the last look, in the background. This is clear and unambiguous, though it does not explicitly name sibling tools or contrast itself with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool and explains when to set force=true, but it does not provide explicit guidance on when to prefer this over alternatives like get_match_status or list_matching_jobs. The 'idempotent and cheap when nothing is new' line gives useful context but stops short of explicit when-to-use or when-not-to-use wording.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tool purposes are generally distinct and well-described, but a few clusters overlap in function: answer_screening_question vs save_answer both write to the answer book, get_my_profile vs get_account both report plan status, and the CV preview/sent-CV/base-CV tools could be confused. The detailed descriptions mitigate most misselection, so this is only a minor issue.
The set almost uniformly uses snake_case verb_noun names like list_, get_, update_, create_, delete_, and start_/stop_. Minor deviations such as login, describe_what_i_want, and the get_my_* vs list_* alternation prevent a perfect score, but the overall pattern is predictable and readable.
49 tools is far above the 25+ threshold and will burden agent tool selection even though many are legitimate single-purpose operations. Several groups could be consolidated—billing links, API-key management, and the CV PDF family—without hurting clarity.
The surface covers the full lifecycle: account creation/auth, profile and CV, targeting, matching, apply runs, screening answers, tracking, billing, export, and deletion. Minor gaps remain, such as no application-level detail/withdrawal endpoint and no direct way to save a parsed CV without re-uploading, but agents can work around them.